Method and apparatus for evaluating fraud risk in an electronic commerce transaction
First Claim
1. A method for evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant using electronic communication, the method comprising:
- receiving transaction information;
applying the transaction information to one or more fraud risk mathematical models wherein each mathematical model produces a respective raw score; and
transforming the one or more respective raw scores with respective sigmoidal functions to generate respective risk estimates.
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Accused Products
Abstract
According to one aspect, transaction information is received and applied to multiple fraud risk mathematical models that each produce a respective raw score, which are transformed with respective sigmoidal transform functions to produce optimized likelihood of fraud risk estimates to provide to a merchant. In one embodiment, the respective fraud risk estimates are combined using fusion proportions that are associated with the respective risk estimates, producing a single point risk estimate, which is transformed with a sigmoidal function to produce an optimized single point risk estimate for the transaction. The sigmoidal functions are derived to approximate a relationship between risk estimates produced by fraud risk detection models and a percentage of transactions associated with respective risk estimates, where the relationship is represented in terms of real-world distributions of fraudulent transaction and non-fraudulent transaction. One embodiment is directed to computing respective risk test penalties for multiple risk tests in one or more of the multiple fraud risk mathematical models used to estimate the likelihood of fraud, given a certain pattern of events represented by the transaction information, wherein the respective risk test penalties are computed as the inverse of the sum of one and a false positive ratio for the respective risk test.
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Citations
40 Claims
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1. A method for evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant using electronic communication, the method comprising:
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receiving transaction information;
applying the transaction information to one or more fraud risk mathematical models wherein each mathematical model produces a respective raw score; and
transforming the one or more respective raw scores with respective sigmoidal functions to generate respective risk estimates. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39)
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12. A method for assessing the likelihood of fraud given a fraud detection response from a fraud risk test in a fraud risk detection mathematical model, the method comprising the step of:
computing a fraud risk test penalty equal to the inverse of the sum of one and a false positive ratio for the fraud risk test, wherein the false positive ratio is a ratio of correct risk detections to incorrect referrals generated by the fraud risk test.
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13. A method for programmatically evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant via a network, the method comprising:
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receiving purchasing information at a server via the network, wherein at least some of the purchasing information is provided by a prospective purchaser of goods or services or goods and services from the merchant;
computing a respective raw score from one or more fraud risk mathematical models, wherein each respective raw score is based at least in part on the purchasing information;
accessing first transformation information from a database to generate one or more first sigmoidal functions that are based at least in part on historical transaction information;
computing a respective risk estimate by transforming a raw score with a respective sigmoidal function;
if there are multiple risk estimates, combining respective risk estimates using fusion proportions to produce a single point risk estimate for the electronic transaction;
accessing second transformation information from a database to generate a second sigmoidal function;
computing an optimized single point risk estimate for the transaction by transforming the single point risk estimate with the second sigmoidal function; and
transmitting a representation of the optimized single point risk estimate to the merchant via the network.
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14. A computer-readable medium carrying one or more sequences of instructions for evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant using electronic communication, which instructions, when executed by one or more processors, cause the one or more processors to carry out the steps of:
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receiving transaction information;
applying the transaction information to one or more fraud risk mathematical models wherein each mathematical model produces a respective raw score; and
transforming the one or more respective raw scores with respective sigmoidal functions to generate respective risk estimates.
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25. A computer-readable medium carrying one or more sequences of instructions for assessing the likelihood of fraud given a fraud detection response from a fraud risk test in a fraud risk detection mathematical model, which instructions, when executed by one or more processors, cause the one or more processors to carry out the steps of:
computing a fraud risk test penalty equal to the inverse of the sum of one and a false positive ratio for the fraud risk test, wherein the false positive ratio is a ratio of correct risk detections to incorrect referrals generated by the fraud risk test.
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26. A computer-readable medium carrying one or more sequences of instructions for programmatically evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant via a network, which instructions, when executed by one or more processors, cause the one or more processors to carry out the steps of:
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receiving purchasing information at a server via the network, wherein at least some of the purchasing information is provided by a prospective purchaser of goods or services or goods and services from the merchant;
computing a respective raw score from one or more fraud risk mathematical models, wherein each respective raw score is based at least in part on the purchasing information;
accessing first transformation information from a database to generate one or more first sigmoidal functions that are based at least in part on historical transaction information;
computing a respective risk estimate by transforming a raw score with a respective sigmoidal function;
if there are multiple risk estimates, combining respective risk estimates using fusion proportions to produce a single point risk estimate for the electronic transaction;
accessing second transformation information from a database to generate a second sigmoidal function;
computing an optimized single point risk estimate for the transaction by transforming the single point risk estimate with the second sigmoidal function; and
transmitting a representation of the optimized single point risk estimate to the merchant via the network.
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27. An apparatus for evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant using electronic communication, comprising:
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means for receiving transaction information;
means for applying the transaction information to one or more fraud risk mathematical models wherein each mathematical model produces a respective raw score, and means for transforming the one or more respective raw scores with respective sigmoidal functions to generate respective risk estimates.
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28. An apparatus for programmatically evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant via a network, comprising:
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means for receiving purchasing information at a server via the network, wherein at least some of the purchasing information is provided by a prospective purchaser of goods or services or goods and services from the merchant;
means for computing a respective raw score from one or more fraud risk mathematical models, wherein each respective raw score is based at least in part on the purchasing information;
means for accessing first transformation information from a database to generate one or more first sigmoidal functions that are based at least in part on historical transaction information;
means for computing a respective risk estimate by transforming a raw score with a respective sigmoidal function;
means for combining respective risk estimates using fusion proportions to produce a single point risk estimate for the electronic transaction, if there are multiple risk estimates;
means for accessing second transformation information from a database to generate a second sigmoidal function;
means for computing an optimized single point risk estimate for the transaction by transforming the single point risk estimate with the second sigmoidal function; and
means for transmitting a representation of the optimized single point risk estimate to the merchant via the network.
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29. An apparatus for evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant using electronic communication, comprising:
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a network interface that is coupled to the data network for receiving one or more packet flows therefrom;
a processor;
one or more stored sequences of instructions which, when executed by the processor, cause the processor to carry out the steps of;
receiving transaction information;
applying the transaction information to one or more fraud risk mathematical models wherein each mathematical model produces a respective raw score; and
transforming the one or more respective raw scores with respective sigmoidal functions to generate respective risk estimates.
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40. An apparatus for programmatically evaluating fraud risk in an electronic commerce transaction and providing a representation of the fraud risk to a merchant via a network, comprising:
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a network interface that is coupled to the data network for receiving one or more packet flows therefrom;
a processor;
one or more stored sequences of instructions which, when executed by the processor, cause the processor to carry out the steps of;
receiving purchasing information at a server via the network, wherein at least some of the purchasing information is provided by a prospective purchaser of goods or services or goods and services from the merchant;
computing a respective raw score from one or more fraud risk mathematical models, wherein each respective raw score is based at least in part on the purchasing information;
accessing first transformation information from a database to generate one or more first sigmoidal functions that are based at least in part on historical transaction information;
computing a respective risk estimate by transforming a raw score with a respective sigmoidal function;
if there are multiple risk estimates, combining respective risk estimates using fusion proportions to produce a single point risk estimate for the electronic transaction;
accessing second transformation information from a database to generate a second sigmoidal function;
computing an optimized single point risk estimate for the transaction by transforming the single point risk estimate with the second sigmoidal function; and
transmitting a representation of the optimized single point risk estimate to the merchant via the network.
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Specification